Transcriptional Profiling of Long Non-Coding Rnas and Novel
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Brunner et al. Genome Biology 2012, 13:R75 http://genomebiology.com/2012/13/8/R75 RESEARCH Open Access Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers Alayne L Brunner1, Andrew H Beck1,2, Badreddin Edris1,3, Robert T Sweeney1, Shirley X Zhu1, Rui Li1, Kelli Montgomery1, Sushama Varma1, Thea Gilks1, Xiangqian Guo1, Joseph W Foley3, Daniela M Witten4, Craig P Giacomini1,5, Ryan A Flynn6, Jonathan R Pollack1, Robert Tibshirani7,8, Howard Y Chang6, Matt van de Rijn1 and Robert B West1* Abstract Background: Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis. Long non-coding RNAs, as a new, relatively unstudied class of transcripts, provide a rich opportunity to identify both functional drivers and cancer-type-specific biomarkers. However, despite the potential importance of long non-coding RNAs to the cancer field, no comprehensive survey of long non-coding RNA expression across various cancers has been reported. Results: We performed a sequencing-based transcriptional survey of both known long non-coding RNAs and novel intergenic transcripts across a panel of 64 archival tumor samples comprising 17 diagnostic subtypes of adenocarcinomas, squamous cell carcinomas and sarcomas. We identified hundreds of transcripts from among the known 1,065 long non-coding RNAs surveyed that showed variability in transcript levels between the tumor types and are therefore potential biomarker candidates. We discovered 1,071 novel intergenic transcribed regions and demonstrate that these show similar patterns of variability between tumor types. We found that many of these differentially expressed cancer transcripts are also expressed in normal tissues. One such novel transcript specifically expressed in breast tissue was further evaluated using RNA in situ hybridization on a panel of breast tumors. It was shown to correlate with low tumor grade and estrogen receptor expression, thereby representing a potentially important new breast cancer biomarker. Conclusions: This study provides the first large survey of long non-coding RNA expression within a panel of solid cancers and also identifies a number of novel transcribed regions differentially expressed across distinct cancer types that represent candidate biomarkers for future research. Keywords: 3SEQ, FFPE, human cancer, intergenic transcripts, lncRNAs, novel transcripts, solid tumors, transcriptional profiling Background cancers have been studied by gene microarrays, protein- The differentially expressed genes from hundreds of can- coding genes have been well studied in this context. cer profiling studies over the last several years have yielded Recent studies looking beyond protein-coding genes have numerous biomarkers that have improved the subtyping, shown that microRNAs (miRNAs) can show higher speci- classification and diagnosis of tumors for both research ficity as biomarkers for some applications than protein- and the clinic [1-3]. Because of the extent to which coding genes. As the landscape of long non-coding RNAs (lncRNAs) grows, studies have found that lncRNAs also * Correspondence: [email protected] tend to show more tissue-specific expression than protein- 1Department of Pathology, Stanford University School of Medicine, 269 coding genes [4]. This property of lncRNAs makes them Campus Drive, Stanford, CA 94305-5324, USA highly attractive as tissue-specific biomarkers. Full list of author information is available at the end of the article © 2012 Brunner et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Brunner et al. Genome Biology 2012, 13:R75 Page 2 of 13 http://genomebiology.com/2012/13/8/R75 LncRNAs, generally defined as having a size greater than quantification (3SEQ) [21,22]. This variation on the tradi- 200 nucleotides, make up a diverse group of non-coding tional RNAseq method enriches for 3’ ends of transcripts RNAs that are distinct from miRNAs. Until recently, very by relying on polyA+ selection of fragmented RNA. Only few lncRNAs were annotated within the human genome. the 3’-end-most polyadenylated fragment of each tran- Now, various groups have developed independent catalogs script is isolated and sequenced, making the technique of human lncRNAs [4-11]. These range from the lncRNA especially suitable for archived samples with fragmented database containing a few hundred high-confidence, RNA. This ‘sequence tag’ approach (not unlike expressed experimentally validated lncRNAs [12] to the largest of the sequence tag (EST) libraries) also significantly reduces the lncRNA catalogs, compiled by the GENCODE group, who sequencing depth necessary relative to RNAseq, because combined manual curation, computational analysis and RNAseq targets the entire length of each transcript. By targeted experimental validation of the GENCODE tran- reducing the sequencing to only a 3’ fragment from each script database to predict more than 14,000 lncRNA tran- transcript using a polyA+ selection, 3SEQ allowed us to scripts from roughly 9,000 gene loci [5,13]. Despite the substantially reduce the depth of sequencing required to thousands of human lncRNAs now predicted, few discover and quantify rare RNAs and allowed us to profile lncRNAs have been well characterized to date, so little is many more samples than would have been possible using known about the expression patterns of most lncRNAs in traditional RNAseq. Additionally, because of its strand- more than a handful of cell types. specific libraries, 3SEQ also provided directional infor- Recent analyses suggest that lncRNAs may play key roles mation for each sequence read, allowing separate in cancer [14,15]. LncRNAs have been shown to play an quantification of transcripts on both strands. important role in epigenetic gene regulation and cellular Given our interest in exploring lncRNA expression differentiation [16-18], both of which are processes fre- across a broad range of solid tumors and identifying new quently deregulated in cancer. Targeted evaluation of the transcripts associated with various cancer types, we chose lncRNA Hox antisense intergenic RNA (HOTAIR) in a set to profile a diverse set of solid human tumors representing of clinical breast cancer specimens showed that HOTAIR adenocarcinomas and squamous cell carcinomas from dif- expression was associated with breast cancer metastasis ferent organs, as well as a variety of soft-tissue sarcomas. and acts by disrupting polycomb repressive complex Although all of these cancer subtypes have been pre- 2-dependent gene silencing [19,20]. Despite the growing viously evaluated by gene microarray, this study represents expectation that numerous lncRNAs are important regula- the first unbiased sequencing-based screen for lncRNAs tors within both normal and cancer biology, no study to and other long novel transcripts across this diverse set of date has performed a survey of lncRNA expression across cancer subtypes. a broad range of human cancer types. We hypothesized that the usage of lncRNAs may be different between nor- Results mal tissues and cancer as well as between various cancers. 3SEQ profiling of lncRNAs and novel transcribed regions To address this, we chose to profile lncRNA expression To profile known lncRNAs as well as identify and quanti- across a range of primary human tumors and compare tate novel transcripts across a range of solid cancers, we expression patterns against a small sampling of normal tis- performed 3SEQ, a 3’-strand-specific sequencing technique sues. A broad collection of cancers offers a rich resource for the quantification of polyA+ RNA [21], to obtain global for studying the usage of known lncRNAs across a range gene expression patterns in 64 solid tumors, representing of cancer biologies and also provides the opportunity to 17 diagnostic classes of both sarcomas and carcinomas. identify new lncRNA candidates. Over 1.7 billion total short sequence reads were generated, High-throughput sequencing provides a number of resulting in more than 409 million reads that mapped advantages over other profiling methods for this type of uniquely to the human genome (Table S1 in Additional study. Sequencing of polyA+ RNA from the various cancer file 1). Because the 3SEQ method captures only the 3’ samples allows for the profiling of transcriptional patterns polyadenylated ends of RNA fragments and directionally ofprotein-codingmRNAsaswellasbothknownand sequences the start of the fragments, the resulting sequen- novel lncRNAs, and any other relatively long polyadeny- cing reads cluster into strand-specific peaks when mapped lated transcripts. Traditional RNA sequencing (RNAseq) to the reference human genome. Initial analysis of the has limitations when profiling numerous primary tumor uniquely mapping reads from the 66 libraries (two tumor samples, including the need for high quality RNA, which samples had duplicate libraries) demonstrated that most is difficult to obtain from formalin-fixed clinical speci- sample libraries possessed reads from at least 24,000 of the mens, and the expense associated with deep sequencing of 37,576 RefSeq transcripts, and this number did not many samples. increase significantly with deeper sequencing